Overview
The images obtained by a Russian photographer by investing the photos he once took
with red, green and blue filters are presented digitally in grayscale format. In this
assignment, we will try to combine and colorize these submitted photos. We will also make
various improvements using some algorithms.
Details of Approach
- With the opencv library, the methods of reading pictures and making changes in
pixels thanks to matrices were comprehended.
- Frames in the picture removed by cutting a certain percentage of the picture
- A single image file contains information of 3 different color channels. So by dividing
the picture into 3 equal parts, I brought it to a state where we can combine the
channels. Example below:
- I used gaussian blur for each channel to reduce noise in pictures
- After dividing the pictures into three and blurring them, we obtained a score by
exhaustive search with the NCC method in order to best match the three pictures
to each other. We aligned the pictures, identifying the best situation.
- After the best alignment was set i combined the r, g, b channels and got a colorized
picture
- After all these processes, I used various algorithms to make the pictures better and
to experiment with them. These are:
ï‚· Gamma Correction
ï‚· Laplacian Filtering
ï‚· Histogram Equalization
The results at the end of all these steps are below.
1 -> not aligned image
2 -> gaussian blurred image
3 -> blurred and aligned image
4 -> plus laplacian filtered image